def _run_segmentation(self):
self.subsegments_manifest_path = os.path.join(self._speaker_dir, 'subsegments.json')
self.subsegments_manifest_path = segments_manifest_to_subsegments_manifest(
segments_manifest_file=self._speaker_manifest_path,
subsegments_manifest_file=self.subsegments_manifest_path,
window=self._speaker_params.window_length_in_sec,
shift=self._speaker_params.shift_length_in_sec,
)
return None
def _run_segmentation(self, window: float, shift: float, scale_tag: str = ''):
self.subsegments_manifest_path = os.path.join(self._speaker_dir, f'subsegments{scale_tag}.json')
logging.info(
f"Subsegmentation for embedding extraction:{scale_tag.replace('_',' ')}, {self.subsegments_manifest_path}"
)
self.subsegments_manifest_path = segments_manifest_to_subsegments_manifest(
segments_manifest_file=self._speaker_manifest_path,
subsegments_manifest_file=self.subsegments_manifest_path,
window=window,
shift=shift,
)
return None
def diarize(self, paths2audio_files: List[str] = None, batch_size: int = 1):
"""
"""
if paths2audio_files:
self.paths2audio_files = paths2audio_files
else:
if self._cfg.diarizer.paths2audio_files is None:
raise ValueError("Pass path2audio files either through config or to diarize method")
else:
self.paths2audio_files = self._cfg.diarizer.paths2audio_files
if type(self.paths2audio_files) is str and os.path.isfile(self.paths2audio_files):
paths2audio_files = []
with open(self.paths2audio_files, 'r') as path2file:
for audiofile in path2file.readlines():
audiofile = audiofile.strip()
paths2audio_files.append(audiofile)
elif type(self.paths2audio_files) in [list, ListConfig]:
paths2audio_files = list(self.paths2audio_files)
else:
raise ValueError("paths2audio_files must be of type list or path to file containing audio files")
self.AUDIO_RTTM_MAP = audio_rttm_map(paths2audio_files, self._cfg.diarizer.path2groundtruth_rttm_files)
if self.has_vad_model:
logging.info("Performing VAD")
mfst_file = self.path2audio_files_to_manifest(paths2audio_files)
self._dont_auto_split = False
self._split_duration = 50
manifest_vad_input = mfst_file
if not self._dont_auto_split:
logging.info("Split long audio file to avoid CUDA memory issue")
logging.debug("Try smaller split_duration if you still have CUDA memory issue")
config = {
'manifest_filepath': mfst_file,
'time_length': self._vad_window_length_in_sec,
'split_duration': self._split_duration,
'num_workers': self._cfg.num_workers,
}
manifest_vad_input = prepare_manifest(config)
else:
logging.warning(
"If you encounter CUDA memory issue, try splitting manifest entry by split_duration to avoid it."
)
self._setup_vad_test_data(manifest_vad_input)
self._run_vad(manifest_vad_input)
else:
if not os.path.exists(self._speaker_manifest_path):
raise NotFoundError("Oracle VAD based manifest file not found")
self.subsegments_manifest_path = os.path.join(self._out_dir, 'subsegments.json')
self.subsegments_manifest_path = segments_manifest_to_subsegments_manifest(
segments_manifest_file=self._speaker_manifest_path,
subsegments_manifest_file=self.subsegments_manifest_path,
window=self._cfg.diarizer.speaker_embeddings.window_length_in_sec,
shift=self._cfg.diarizer.speaker_embeddings.shift_length_in_sec,
)
self._extract_embeddings(self.subsegments_manifest_path)
out_rttm_dir = os.path.join(self._out_dir, 'pred_rttms')
os.makedirs(out_rttm_dir, exist_ok=True)
perform_diarization(
embeddings_file=self._embeddings_file,
reco2num=self._num_speakers,
manifest_path=self.subsegments_manifest_path,
audio_rttm_map=self.AUDIO_RTTM_MAP,
out_rttm_dir=out_rttm_dir,
max_num_speakers=self.max_num_speakers,
)